Web based health surveys: Using a Two Step Heckman model to examine their potential for population health analysis
Morrissey, KM; Kinderman, Peter; Pontin, Eleanor; et al.Tai, Sara; Schwannauer, Mathias
Date: 1 June 2016
Journal
Social science & medicine
Publisher
Elsevier
Publisher DOI
Abstract
In June 2011 the BBC Lab UK carried out a web-based survey on the causes of mental
distress. The ‘Stress Test’ was launched on ‘All in the Mind’ a BBC Radio 4 programme and
the test’s URL was publicised on radio and TV broadcasts, and made available via BBC web
pages and social media. Given the large amount of data created, over ...
In June 2011 the BBC Lab UK carried out a web-based survey on the causes of mental
distress. The ‘Stress Test’ was launched on ‘All in the Mind’ a BBC Radio 4 programme and
the test’s URL was publicised on radio and TV broadcasts, and made available via BBC web
pages and social media. Given the large amount of data created, over 32,800 participants,
with corresponding diagnosis, demographic and socioeconomic characteristics; the dataset
are potentially an important source of data for population based research on depression and
anxiety. However, as respondents self-selected to participate in the online survey, the
survey may comprise a non-random sample. It may be only individuals that listen to BBC
Radio 4 and/or use their website that participated in the survey. In this instance using the
Stress Test data for wider population based research may create sample selection bias.
Focusing on the depression component of the Stress Test, this paper presents an easy-to-use
method, the Two Step Probit Selection Model, to detect and statistically correct selection
bias in the Stress Test. Using a Two Step Probit Selection Model; this paper did not find a
statistically significant selection on unobserved factors for participants of the Stress Test.
That is, survey participants who accessed and completed an online survey are not
systematically different from non-participants on the variables of substantive interest.
Institute of Health Research
Collections of Former Colleges
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